I am working on a critically endangered bustard species in India (Houbaropsis bengalensis). I need to prepare a land cover map of its 'suitable' grassland habitat across its distributional range. I have points (and can construct polygons from them using Google Earth's help) where 'suitable' (for the species) grasslands exist since I did presence/not detected surveys in its distribution range.
Since the very same region also has a great amount of cultivation activity, sometimes land cover maps resulting just from the spectral signature using supervised classification tends to pick up croplands as 'grasslands'.
In order to avoid this obviously erroneous assessment, we (myself and collaborators) thought that using a temporal-spectral signature might be a better thing to do since croplands experience this sudden dip in NDVI when harvested and till new crops are sown (they may also have multiple cropping within a year), whereas grasslands do not (well...grasslands too are burnt once a year as a habitat management practice).
May I request people on this forum to help me in making a more detailed land cover map of this study area(s)/distribution range using temporal-spectral signatures in a supervised/unsupervised classification framework in order to distinguish between otherwise similar land cover types such as that in my case (natural/semi-natural grassland and cropland)? Is it even possible to do this in QGIS entirely, or perhaps using the interface of R and QGIS?
Please note that I would be using PROBA-V NDVI (333metre resolution) data for this.